Blocking and Randomization for Experimental Design
Alternative acceptance function for multi-dimensional scores in which ...
Default acceptance function. Accept current score if and only if all e...
Compare two data.frames.
Distributes samples based on a sample sheet.
Distributes samples in order.
Assignment function which distributes samples randomly.
Creates a BatchContainer from a table (data.frame /tibble::tibble ) co...
R6 Class representing a batch container.
R6 Class representing a batch container dimension.
Compile list of all possible ways to assign levels of the allocation v...
Reshuffle sample indices completely randomly
designit: Blocking and Randomization for Experimental Design
Show that the package is designed to rely on data.table functionality
Drop highest order interactions
Extract relevant parameters from a generic shuffle function output
Internal function to generate possible subgroup combinations that add ...
Aggregation of scores: take first (primary) score only
Form groups and subgroups of 'homogeneous' samples as defined by certa...
Generate terms.object (formula with attributes)
Get highest order interaction
Aggregation of scores: L1 norm
Aggregation of scores: L2 norm squared
Create locations table from dimensions and exclude table
Make matrix column names unique.
Create a function that transforms a current (multi-dimensional) score ...
Create function to propose n pairwise swaps of samples on each call (n...
Internal helper function to set up an (n m) x (n m) pairwise distance ...
Alternative acceptance function for multi-dimensional scores with expo...
Create a list of scoring functions (one per plate) that quantify the s...
Generate acceptance function for an optimization protocol based on sim...
Create a temperature function that returns the annealing temperature a...
Created a shuffling function that permutes samples within certain subg...
Create function to propose swaps of samples on each call, either with ...
Generic optimizer that can be customized by user provided functions fo...
Convenience wrapper to optimize a typical multi-plate design
Compute OSAT score for sample assignment.
Convenience wrapper for the OSAT score
Proposes pairwise swap of samples on each call.
Plot plate layouts
Estimate the variance of individual scores by a series of completely r...
Helper function to print out one set of scores plus (if needed) aggreg...
Sample scores from a number of completely random sample permutations
Shrinks a matrix with scores and adds an iteration column.
Generate in one go a shuffling function that produces permutations wit...
Shuffling proposal function with constraints.
Compose shuffling function based on already available subgrouping and ...
Acceptance probability for a new solution
Aggregation of scores: sum up all individual scores
Updates a batch container by permuting samples according to a shufflin...
Validates sample data.frame.
Validate subgroup object and stop with error message if not all requir...
Aggregation of scores: take the maximum (i.e. worst score only)
Intelligently assign samples to batches in order to reduce batch effects. Batch effects can have a significant impact on data analysis, especially when the assignment of samples to batches coincides with the contrast groups being studied. By defining a batch container and a scoring function that reflects the contrasts, this package allows users to assign samples in a way that minimizes the potential impact of batch effects on the comparison of interest. Among other functionality, we provide an implementation for OSAT score by Yan et al. (2012, <doi:10.1186/1471-2164-13-689>).
Useful links